The use of light scattering measurements as a means for differentiating various types of small particles is well known. For example, in virtually all sophisticated hematology instruments, it is common to measure the forward light scattering properties of blood cells by passing the cells, one at a time, through the interrogation zone of an optical flow cell. While in the interrogation zone, each cell is irradiated by a laser beam, and one or more photodetectors, strategically positioned forward of the interrogation zone, operate to sense the level of forward scattered radiation, often within several different predetermined angular ranges. In addition to measuring forward light scatter, some hematology instruments measure side scatter as well, using a separate photodetector located orthogonally of the irradiated cell. These light scattering measurements are often combined with other simultaneously made measurements to better differentiate cell types of particular interest from other cells and other particulate material within the sample that have similar light-scattering properties within the angular ranges measured. These other simultaneously-made measurements include those representing the cell's physical volume, its electrical conductivity, and its effectiveness in attenuating the irradiating beam by virtue of its presence in the beam (sometimes referred to as the axial light loss (ALL) of a cell). Having made various cell parameter measurements, the instrument then produces scattergrams in which the different parameters measured are plotted against each other. Ideally, each sub-population of cells of the same type appears in these scattergrams as a tight cluster of data points, each point representing an individual cell, and each cluster being readily identifiable from other clusters by a clearly identified spacing between the clusters. In such case, it is a simple matter to “gate” cells of one cluster from those of another cluster and to enumerate the cells of each type within the gate. Unfortunately, this ideal is sometimes difficult to realize since, for many reasons, a small percentage of cells of one type invariably invade the spatial domain of cells of other types, thereby making the cell count of a cell type of interest somewhat imprecise. As noted below, this is especially true in the case of platelet and basophil differentiation.
In an article entitled “Flow Cytometric Measurement of Platelet Function and Reticulated Platelets,” by Kenneth A. Ault, Annals New York Academy of Sciences, 677:293-308 (1993), the importance of platelet analyses for clinical applications is discussed. This article also discusses the problem of identifying and enumerating platelets using conventional light-scattering techniques. It is noted that the concentration of platelets in a normal whole blood sample is relatively high, being second only to the concentration of red blood cells (erythrocytes). One milliliter of blood normally contains about 250 million platelets. Thus, while they are about 20 times less frequent than red cells, platelets are about 25 times more frequent than all types of white cells (leukocytes) combined. While their normal size range (1 to 4 microns) enables platelets to be readily identified from other types of normal cells in a blood sample, their cluster in a scattergram usually contains a large amount of cellular debris (fragments of all cells) that “look like” platelets in terms of their normally measured volume and forward light scattering properties. Ault notes an uncertainty in differentiating platelets from cell debris on the basis of forward and side-scatter measurements alone, and he describes a more reliable technique based on both forward light scatter and fluorescence measurements. While the light scatter/fluorescence technique described by Ault does provide a more positive identification of platelets than the noted light scatter alone technique, this technique requires the additional step of selectively tagging or labeling platelets with fluorescent dye molecules, either directly or via suitable monoclonal antibodies that have been tagged with a fluorescent marker. This tagging step, of course, is both time-consuming and costly. Further, this tagging of platelets subjects the platelets to considerable agitation or manipulation, which has an undesired effect on platelet activation.
In U.S. Pat. No. 6,025,201 to D. Zelmanovic et al., several different techniques for differentiating and counting platelets are noted. The patent disclosure is directed to a method for assessing the activation state of platelets by determining their respective dry mass and refractive index. A preferred method comprises the steps of measuring the forward light-scatter of platelets irradiated by a laser beam within two different light scatter ranges, a low range of between 1 and 7 degrees, and a high range of between 5 and 20 degrees. Alternatively, the forward light-scatter measured within one of the two preferred scatter ranges is combined with a DC volume measurement, and a Mie Scattering Theory-based analysis is performed to provide platelet counting and analysis. This platelet analysis scheme is considered advantageous over the above-noted Ault technique in that it lends itself to full automation, requiring no off-line sample preparation for fluorescent tagging purposes. The same can be said, of course, for the many different fully-automated platelet analysis techniques used commercially to date. These techniques include (a) the total impedance scheme (used in the Model STKS™ and Model GEN•S™ blood analyzers manufactured and sold by the assignee hereof) where platelet volume is determined by monitoring the change in electrical impedance of a restricted aperture caused by a platelet passing through it; (b) the total light-scatter scheme (used in the TECHNICON H* System instrument made and sold by Bayer, and in the ORTHO ELT-8 instrument made and sold by Ortho Diagnostics) where the intensity of forward scattered light is monitored within one or more angular ranges, such scatter intensity being proportional to platelet volume; and (c) the combined impedance and light scatter scheme used in the Cell-Dyn® 4000 blood analyzer made and sold by Abbott Laboratories) where cell volume is determined both electrically (via aperture impedance) and optically (via forward light scatter) simultaneously. As indicated above, however, all of these schemes are susceptible to cross-contamination by non-platelets, introducing a certain degree of uncertainty in the data reported. The impedance approach is problematic in that any cell debris having a volume similar to that of a normal platelet will be displayed and counted as a platelet. The forward scatter approach is problematic in that cellular debris of the same size or volume as a platelet will produce a forward-scatter signature similar to a platelet and thereby be counted as a platelet. Further, in making such light scatter measurements, it is common to use relatively large surface area photodetectors (typically pin diodes) to collect the scattered light. Unfortunately, such large detectors are problematic in that they also collect stray light reflected by various surfaces within the optical system and thereby produce signals having a relatively low signal-to-noise ratio. Even when shaped to exclude the collection of stray light (e.g., shaped as a circular ring centered about the irradiating beam axis), these photodetectors still require a substantial surface area to achieve the gain necessary to sense the scattered radiation, and the larger the surface area, the slower the electrical response time. Schemes that combine the electrical and optical techniques are subject to the same disadvantages of each approach. Further, they are disadvantageous in that apparatus must be provided for making both electrical and optical measurements.
As regards conventional techniques for identifying and quantifying the basophil sub-population of white cells in a blood sample, uncertainties can arise in the numbers reported not only because of the very small number of these cells in the sample (being substantially less than one per cent of the leukocyte population) but also because of their similarity in physical and electrical properties with the relatively plentiful monocyte and lymphocyte sub-populations. Typically, a combination of forward-angle light-scatter, and RF conductivity, and DC impedance measurements are made to differentiate basophils from other cell types, as is the case in the STKS™ and GEN•S™ Blood Analyzers, made and sold by Beckman Coulter, Inc. Alternatively, forward angle measurements have been combined with polarized side-scatter measurements to differentiate basophils, as is the case in the Cell-Dyn hematology instruments made and sold by Abbott Laboratories. Neither technique can be said to be optimum. The former is disadvantageous as requiring an RF circuit for establishing a high-frequency current flow through the cell-interrogation zone, whereby changes in the current through the zone, as occasioned by the passage of blood cells and/or particles of differing impedance characteristics, can be monitored. Both techniques are problematic in that the optical coupling efficiency between the light-scattering particle and the large surface area detectors commonly used to detect the scattered light is low.
It has been suggested that multiple bundles of fiber optics, arranged in concentric rings, can be used to optically couple scattered radiation from a scatter plane to multiple photodetectors (e.g., photomultiplier tubes and photodiodes) remotely spaced from the scatter plane. See, “Cell Differentiation Based on Absorption and Scattering” by Wolfgang G. Eisert, The Journal of Histology and Cytochemistry, Vol.27, No.1, pp404-409 (1979). As described by Eisert, optical fibers are arranged so that their respective light-collecting ends form five concentric rings centered about a centrally located light-collecting bundle of optical fibers. The respective distal ends of the individual fibers of each of the five concentric rings are optically coupled to five different photomultiplier tubes, and the distal ends of the individual fibers of the center bundle are optically coupled to a photodiode. The center bundle of fibers is optically aligned with the beam axis, and the other bundles, with their individual fibers being arranged in a circle, are also arranged parallel to the beam axis. Thus, each ring of fibers collects scattered light in a discrete angular range determined by the diameter of the fiber (or the width of the rings), the radial displacement of the fiber end relative to the beam axis (i.e., the diameter of the ring), and the axial spacing of the fiber ends from the scattering light source. The sixth and center bundle of fiber optics, being positioned on the beam axis, serves to monitor the axial light loss of the beam, as occasioned by the passage of cells therethrough.
In the fiber-optic light coupler proposed by Eisert above, the respective light-collecting ends of all the fibers are disposed in a common plane that is arranged perpendicular to the optical axis of the cell-irradiating light beam. Thus, it will be appreciated that, due to the numerical aperture of the fibers, the optical coupling of scattered light into the optical fibers deteriorates as the scatter angle increases. Additionally, as the scatter angle increases, the angle of incidence between the scattered light and the fiber end increases, thereby increasing the number of internal reflections required to transmit the scattered light from one end of the fiber to the other end. This problem of coupling efficiency is exacerbated by the dramatic reduction in scatter intensity at relatively large scatter angles.
In addition to forward- and side-scatter measurements, it has been suggested that back-scatter (i.e., reflected light) measurements may prove useful in differentiating blood cell types. In a theoretical paper entitled, “Elastic Light Scattering From Nucleated Blood Cells: Rapid Numerical Analysis,” by Sloot and Figdor, Applied Optics, Vol. 25, No. 19, 1 Oct. 1986, it is noted that simultaneous detection of the light-scatter intensities in the forward lateral, and backward directions is required to optimize the detection of different cell types in heterogeneous populations of nucleated blood cells. Here, a model is presented to calculate the light-scattering properties of nucleated blood cells which are mimicked by two concentric spheres. It is derived from the calculations presented (no actual measurements on cells were made) that the back-scatter intensity is determined by the nucleus/cytoplasm ratio and changes in the optical density of the cytoplasm and nucleus. The analysis presented strongly suggests a direct correlation between the transparency of the nucleus and the intensity of the back-scatter signal. While no hardware is disclosed in this paper for making any light-scattering measurements at all, a subsequent paper, “Scattering Matrix Elements of Biological Particles Measured in a Flow Through System: Theory and Practice” by Sloot et al., Applied Optics, Vol. 28, No. 10, 15 May 1989, alludes to the use of large surface area scatter detectors and the need to apply “large cone integration” to account for the relatively large surfaces. This paper schematically illustrates a back-scatter detector having a central aperture through which the particle-irradiating laser beam travels before irradiating the particle. Upon striking the particle, the large surface of the back-scatter detector collects and detects back-scattered light through a large cone angle, i.e., throughout a large angular range. As noted above large surface area detectors, while advantageous from the standpoint of optical gain, are highly disadvantageous from a response-time standpoint. As the detector surface area increases, the detector response time decreases, thereby limiting the speed at which the system can resolve cells.